Techniques for pairing contacts and agents in a contact center system

ABSTRACT

Techniques for pairing contacts and agents in a contact center system are disclosed. In one particular embodiment, the techniques may be realized as a method for pairing contacts and agents in a contact center system comprising: assigning, by at least one computer processor communicatively coupled to and configured to operate in the contact center system, a contact to an agent based on information associated with a prior interaction of the contact with the contact center system. The assigning of the contact to the agent may result in a less favorable outcome for the contact assigned to the agent and an increase in an overall performance of the contact center system.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.17/001,376, filed Aug. 24, 2020, which is a continuation of U.S. patentapplication Ser. No. 16/538,288, filed Aug. 12, 2019, now U.S. Pat. No.10,757,261, which is hereby incorporated by reference in its entirety asif fully set forth herein.

FIELD OF THE DISCLOSURE

The present disclosure generally relates to contact center systems, moreparticularly, to techniques for pairing contacts and agents in a contactcenter system.

BACKGROUND OF THE DISCLOSURE

A typical task assignment system algorithmically assigns tasks arrivingat a task assignment center to agents available to handle those tasks.At times, the task assignment center may be in an “L1 state” and haveagents available and waiting for assignment to tasks. At other times,the task assignment center may be in an “L2 state” and have taskswaiting in one or more queues for an agent to become available forassignment. At yet other times, the task assignment system may be in an“L3 state” and have multiple agents available and multiple tasks waitingfor assignment. An example of a task assignment system is a contactcenter system that receives contacts (e.g., telephone calls, internetchat sessions, emails, etc.) to be assigned to agents.

In some typical task assignment centers, tasks are assigned to agentsordered based on time of arrival, and agents receive tasks ordered basedon the time when those agents became available. This strategy may bereferred to as a “first-in, first-out,” “FIFO,” or “round-robin”strategy. For example, in an L2 environment, when an agent becomesavailable, the task at the head of the queue would be selected forassignment to the agent.

In other typical task assignment centers, a performance-based routing(PBR) strategy for prioritizing higher-performing agents for taskassignment may be implemented. Under PBR, for example, thehighest-performing agent among available agents receives the nextavailable task. Other PBR and PBR-like strategies may make assignmentsusing specific information about the agents.

“Behavioral Pairing” or “BP” strategies, for assigning tasks to agents,improve upon traditional assignment methods. BP targets balancedutilization of agents while simultaneously improving overall taskassignment center performance potentially beyond what FIFO or PBRmethods will achieve in practice.

When determining a BP model for a BP strategy, a task assignment systemmay consider information about its agents and incoming tasks or types oftasks. For example, a contact center system may consider the performancehistory of each agent, such as an agent's conversion rate in a salesqueue, and it may consider customer information about a contact, such asthe type of service a customer uses or how many years the customer hashad a contract with the company, and other types of data found in atypical customer relationship management (CRM) system.

In some contact center systems, it may be advantageous for a BP model toaccount for historical information associated with a contact's phonenumber (e.g., billing telephone number (BTN)). Thus, it may beunderstood that there may be a need for a BP model that takes intoconsideration historical information associated with a contact's phonenumber in order to optimize the overall performance of a contact centersystem.

SUMMARY OF THE DISCLOSURE

Techniques for pairing contacts and agents in a contact center systemare disclosed. In one particular embodiment, the techniques may berealized as a method for pairing contacts and agents in a contact centersystem comprising: assigning, by at least one computer processorcommunicatively coupled to and configured to operate in the contactcenter system, a contact to an agent based on information associatedwith a prior interaction of the contact with the contact center system.The assigning of the contact to the agent may result in a less favorableoutcome for the contact assigned to the agent and an increase in anoverall performance of the contact center system.

In accordance with other aspects of this particular embodiment, theinformation may include an amount of time that has elapsed since theprior interaction.

In accordance with other aspects of this particular embodiment, theinformation may include an amount of time that elapsed between the priorinteraction and an interaction of the contact with the contact centersystem that precedes the prior interaction.

In accordance with other aspects of this particular embodiment, theinformation may include a time duration of the prior interaction.

In accordance with other aspects of this particular embodiment, theinformation may include an average time duration of the priorinteraction and one or more interactions of the contact with the contactcenter system that precede the prior interaction.

In accordance with other aspects of this particular embodiment, theinformation may include one or more outcomes from the prior interaction.

In accordance with other aspects of this particular embodiment, theinformation may include a most common outcome from among the priorinteraction and one or more interactions of the contact with the contactcenter system that precede the prior interaction.

In accordance with other aspects of this particular embodiment, theinformation may include at least one of a type, a purpose, a context,and a queue of the prior interaction.

In accordance with other aspects of this particular embodiment, theinformation may include at least one of a most common type, a mostcommon purpose, a most common context, and a most common queue among theprior interaction and one or more interactions of the contact with thecontact center system that precede the prior interaction.

In another particular embodiment, the techniques may be realized as asystem for pairing contacts and agents in a contact center systemcomprising at least one computer processor communicatively coupled toand configured to operate in the task assignment system, wherein the atleast one computer processor is further configured to perform the stepsin the above-described method.

In another particular embodiment, the techniques may be realized as anarticle of manufacture for pairing contacts and agents in a contactcenter system comprising a non-transitory processor readable medium andinstructions stored on the medium, wherein the instructions areconfigured to be readable from the medium by at least one computerprocessor communicatively coupled to and configured to operate in thecontact center system and thereby cause the at least one computerprocessor to operate so as to perform the steps in the above-describedmethod.

The present disclosure will now be described in more detail withreference to particular embodiments thereof as shown in the accompanyingdrawings. While the present disclosure is described below with referenceto particular embodiments, it should be understood that the presentdisclosure is not limited thereto. Those of ordinary skill in the arthaving access to the teachings herein will recognize additionalimplementations, modifications, and embodiments, as well as other fieldsof use, which are within the scope of the present disclosure asdescribed herein, and with respect to which the present disclosure maybe of significant utility.

BRIEF DESCRIPTION OF THE DRAWINGS

To facilitate a fuller understanding of the present disclosure,reference is now made to the accompanying drawings, in which likeelements are referenced with like numerals. These drawings should not beconstrued as limiting the present disclosure, but are intended to beillustrative only.

FIG. 1 shows a block diagram of a task assignment center according toembodiments of the present disclosure.

FIG. 2 shows a block diagram of a task assignment system according toembodiments of the present disclosure.

FIG. 3 shows a flow diagram of a contact assignment method according toembodiments of the present disclosure.

DETAILED DESCRIPTION

A typical task assignment system algorithmically assigns tasks arrivingat a task assignment center to agents available to handle those tasks.At times, the task assignment center may be in an “L1 state” and haveagents available and waiting for assignment to tasks. At other times,the task assignment center may be in an “L2 state” and have taskswaiting in one or more queues for an agent to become available forassignment. At yet other times, the task assignment system may be in an“L3 state” and have multiple agents available and multiple tasks waitingfor assignment. An example of a task assignment system is a contactcenter system that receives contacts (e.g., telephone calls, internetchat sessions, emails, etc.) to be assigned to agents.

In some traditional task assignment centers, tasks are assigned toagents ordered based on time of arrival, and agents receive tasksordered based on the time when those agents became available. Thisstrategy may be referred to as a “first-in, first-out,” “FIFO,” or“round-robin” strategy. For example, in an L2 environment, when an agentbecomes available, the task at the head of the queue would be selectedfor assignment to the agent. In other traditional task assignmentcenters, a performance-based routing (PBR) strategy for prioritizinghigher-performing agents for task assignment may be implemented. UnderPBR, for example, the highest-performing agent among available agentsreceives the next available task.

The present disclosure refers to optimized strategies, such as“Behavioral Pairing” or “BP” strategies, for assigning tasks to agentsthat improve upon traditional assignment methods. BP targets balancedutilization of agents while simultaneously improving overall taskassignment center performance potentially beyond what FIFO or PBRmethods will achieve in practice. This is a remarkable achievementinasmuch as BP acts on the same tasks and same agents as FIFO or PBRmethods, approximately balancing the utilization of agents as FIFOprovides, while improving overall task assignment center performancebeyond what either FIFO or PBR provide in practice. BP improvesperformance by assigning agent and task pairs in a fashion that takesinto consideration the assignment of potential subsequent agent and taskpairs such that, when the benefits of all assignments are aggregated,they may exceed those of FIFO and PBR strategies.

Various BP strategies may be used, such as a diagonal model BP strategyor a network flow BP strategy. These task assignment strategies andothers are described in detail for a contact center context in, e.g.,U.S. Pat. Nos. 9,300,802, 9,781,269, 9,787,841, and 9,930,180, all ofwhich are hereby incorporated by reference herein. BP strategies may beapplied in an L1 environment (agent surplus, one task; select amongmultiple available/idle agents), an L2 environment (task surplus, oneavailable/idle agent; select among multiple tasks in queue), and an L3environment (multiple agents and multiple tasks; select among pairingpermutations).

When determining a BP model for a BP strategy, a task assignment systemmay consider information about its agents and incoming tasks or types oftasks. For example, a contact center system may consider the performancehistory of each agent, such as an agent's conversion rate in a salesqueue, and it may consider customer information about a contact, such asthe type of service a customer uses or how many years the customer hashad a contract with the company, and other types of data found in atypical customer relationship management (CRM) system. As explained indetail below, embodiments of the present disclosure relates to taskassignment systems that may account for historical informationassociated with a contact's phone number (e.g., billing telephone number(BTN)) in determining a BP model.

FIG. 1 shows a block diagram of a task assignment center 100 accordingto embodiments of the present disclosure. The description hereindescribes network elements, computers, and/or components of a system andmethod for pairing strategies in a task assignment system that mayinclude one or more modules. As used herein, the term “module” may beunderstood to refer to computing software, firmware, hardware, and/orvarious combinations thereof. Modules, however, are not to beinterpreted as software which is not implemented on hardware, firmware,or recorded on a non-transitory processor readable recordable storagemedium (i.e., modules are not software per se). It is noted that themodules are exemplary. The modules may be combined, integrated,separated, and/or duplicated to support various applications. Also, afunction described herein as being performed at a particular module maybe performed at one or more other modules and/or by one or more otherdevices instead of or in addition to the function performed at theparticular module. Further, the modules may be implemented acrossmultiple devices and/or other components local or remote to one another.Additionally, the modules may be moved from one device and added toanother device, and/or may be included in both devices.

As shown in FIG. 1, the task assignment center 100 may include a centralswitch 210. The central switch 110 may receive incoming tasks (e.g.,telephone calls, internet chat sessions, emails, etc.) or supportoutbound connections to contacts via a dialer, a telecommunicationsnetwork, or other modules (not shown). The central switch 110 mayinclude routing hardware and software for helping to route tasks amongone or more subcenters, or to one or more Private Branch Exchange(“PBX”) or Automatic Call Distribution (ACD) routing components or otherqueuing or switching components within the task assignment center 100.The central switch 110 may not be necessary if there is only onesubcenter, or if there is only one PBX or ACD routing component in thetask assignment center 100.

If more than one subcenter is part of the task assignment center 100,each subcenter may include at least one switch (e.g., switches 120A and120B). The switches 120A and 120B may be communicatively coupled to thecentral switch 110. Each switch for each subcenter may becommunicatively coupled to a plurality (or “pool”) of agents. Eachswitch may support a certain number of agents (or “seats”) to be loggedin at one time. At any given time, a logged-in agent may be availableand waiting to be connected to a task, or the logged-in agent may beunavailable for any of a number of reasons, such as being connected toanother contact, performing certain post-call functions such as logginginformation about the call, or taking a break. In the example of FIG. 1,the central switch 110 routes tasks to one of two subcenters via switch120A and switch 120B, respectively. Each of the switches 120A and 120Bare shown with two agents each. Agents 130A and 130B may be logged intoswitch 120A, and agents 130C and 130D may be logged into switch 120B.

The task assignment center 100 may also be communicatively coupled to anintegrated service from, for example, a third-party vendor. In theexample of FIG. 1, behavioral pairing module 140 may be communicativelycoupled to one or more switches in the switch system of the taskassignment center 100, such as central switch 110, switch 120A, andswitch 120B. In some embodiments, switches of the task assignment center100 may be communicatively coupled to multiple behavioral pairingmodules. In some embodiments, behavioral pairing module 140 may beembedded within a component of the task assignment center 100 (e.g.,embedded in or otherwise integrated with a switch).

Behavioral pairing module 140 may receive information from a switch(e.g., switch 120A) about agents logged into the switch (e.g., agents130A and 130B) and about incoming tasks via another switch (e.g.,central switch 110) or, in some embodiments, from a network (e.g., theInternet or a telecommunications network) (not shown). The behavioralpairing module 140 may process this information to determine which tasksshould be paired (e.g., matched, assigned, distributed, routed) withwhich agents.

For example, in an L1 state, multiple agents may be available andwaiting for connection to a contact, and a task arrives at the taskassignment center 100 via a network or the central switch 110. Asexplained above, without the behavioral pairing module 140, a switchwill typically automatically distribute the new task to whicheveravailable agent has been waiting the longest amount of time for a taskunder a FIFO strategy, or whichever available agent has been determinedto be the highest-performing agent under a PBR strategy. With abehavioral pairing module 140, contacts and agents may be given scores(e.g., percentiles or percentile ranges/bandwidths) according to apairing model or other artificial intelligence data model, so that atask may be matched, paired, or otherwise connected to a preferredagent.

In an L2 state, multiple tasks are available and waiting for connectionto an agent, and an agent becomes available. These tasks may be queuedin a switch such as a PBX or ACD device. Without the behavioral pairingmodule 140, a switch will typically connect the newly available agent towhichever task has been waiting on hold in the queue for the longestamount of time as in a FIFO strategy or a PBR strategy when agent choiceis not available. In some task assignment centers, priority queuing mayalso be incorporated, as previously explained. With a behavioral pairingmodule 140 in this L2 scenario, as in the L1 state described above,tasks and agents may be given percentiles (or percentileranges/bandwidths, etc.) according to, for example, a model, such as anartificial intelligence model, so that an agent becoming available maybe matched, paired, or otherwise connected to a preferred task.

FIG. 2 shows a block diagram of a task assignment system 200 accordingto embodiments of the present disclosure. The task assignment system 200may be included in a task assignment center (e.g., task assignmentcenter 100) or incorporated in a component or module (e.g., behavioralpairing module 140) of a task assignment center for helping to assigntasks among various agents.

The task assignment system 200 may include a task assignment module 210that is configured to pair (e.g., match, assign) incoming tasks toavailable agents. In the example of FIG. 2, m tasks 220A-220 m arereceived over a given period, and n agents 230A-230 n are availableduring the given period. Each of the m tasks may be assigned to one ofthe n agents for servicing or other types of task processing. In theexample of FIG. 2, m and n may be arbitrarily large finite integersgreater than or equal to one. In a real-world task assignment center,such as a contact center, there may be dozens, hundreds, etc. of agentslogged into the contact center to interact with contacts during a shift,and the contact center may receive dozens, hundreds, thousands, etc. ofcontacts (e.g., telephone calls, interne chat sessions, emails, etc.)during the shift.

In some embodiments, a task assignment strategy module 240 may becommunicatively coupled to and/or configured to operate in the taskassignment system 200. The task assignment strategy module 240 mayimplement one or more task assignment strategies (or “pairingstrategies”) for assigning individual tasks to individual agents (e.g.,pairing contacts with contact center agents). A variety of differenttask assignment strategies may be devised and implemented by the taskassignment strategy module 240. In some embodiments, a FIFO strategy maybe implemented in which, for example, the longest-waiting agent receivesthe next available task (in L1 environments) or the longest-waiting taskis assigned to the next available agent (in L2 environments). In otherembodiments, a PBR strategy for prioritizing higher-performing agentsfor task assignment may be implemented. Under PBR, for example, thehighest-performing agent among available agents receives the nextavailable task. In yet other embodiments, a BP strategy may be used foroptimally assigning tasks to agents using information about either tasksor agents, or both. Various BP strategies may be used, such as adiagonal model BP strategy or a network flow BP strategy. See U.S. Pat.Nos. 9,300,802, 9,781,269, 9,787,841, and 9,930,180.

In some embodiments, a historical assignment module 250 may becommunicatively coupled to and/or configured to operate in the taskassignment system 200 via other modules such as the task assignmentmodule 210 and/or the task assignment strategy module 240. Thehistorical assignment module 250 may be responsible for variousfunctions such as monitoring, storing, retrieving, and/or outputtinginformation about task-agent assignments that have already been made.For example, the historical assignment module 250 may monitor the taskassignment module 210 to collect information about task assignments in agiven period. Each record of a historical task assignment may includeinformation such as an agent identifier, a task or task type identifier,offer or offer set identifier, outcome information, or a pairingstrategy identifier (i.e., an identifier indicating whether a taskassignment was made using a BP strategy, a BP strategy, or some otherpairing strategy such as a FIFO or PBR pairing strategy).

In some embodiments and for some contexts, additional information may bestored. For example, in a call center context, the historical assignmentmodule 250 may also store information about the time a call started, thetime a call ended, the phone number dialed, and the caller's phonenumber. For another example, in a dispatch center (e.g., “truck roll”)context, the historical assignment module 250 may also store informationabout the time a driver (i.e., field agent) departs from the dispatchcenter, the route recommended, the route taken, the estimated traveltime, the actual travel time, the amount of time spent at the customersite handling the customer's task, etc.

In some embodiments, the historical assignment module 250 may generate apairing model, a BP model, or similar computer processor-generated modelbased on a set of historical assignments for a period of time (e.g., thepast week, the past month, the past year, etc.), which may be used bythe task assignment strategy module 240 to make task assignmentrecommendations or instructions to the task assignment module 210.

In some embodiments, the historical assignment module 250 may generate aBP model to account for historical information associated with acontact's phone number (e.g., billing telephone number (BTN)). Forexample, in the context of a contact center system, based on a contact'sphone number, the historical assignment module 250 may include, as avariable or other parameter in the BP model, the amount of time that haselapsed since the contact's prior interaction with the contact centersystem, an average amount of time elapsed in between the contact'sprevious interactions with the contact center system, a duration of thecontact's previous interaction with the contact center system, and/or anaverage duration of the contact's previous interactions with the contactcenter system.

In some embodiments, in a contact center system context, based on acontact's phone number, the historical assignment module 250 mayinclude, as a variable or other parameter in the BP model, one or moreoutcomes associated with the contact's previous interaction(s) with thecontact center system, the most common or average outcome associatedwith the contact's previous interactions with the contact center system,and/or an indication as to whether the contact's current interactionwith the contact center system is the contact's first interaction withthe contact center system. A type, purpose, context, queue, etc. of thecontact's previous interaction with the contact center system, and/orthe most common or average type, purpose, context, queue, etc. of thecontact's previous interactions with the contact center system may alsobe included as a variable or other parameter in the BP model.

As with previously-disclosed BP strategies, a BP strategy, which isbased on a BP model that accounts for historical information associatedwith a contact's phone number, aims at optimizing the overallperformance of the contact center system rather than every individualinstant contact-agent pairing. For instance, in some embodiments, aparticular contact-agent pairing may result in the worst (or lessfavorable) expected instant outcome for the pairing, but in an increasein expected overall performance of the contact center system. In otherembodiments, a particular contact-agent pairing may result in the bestexpected instant outcome for the pairing, and in an increase in expectedoverall performance of the contact center system.

In some embodiments, a benchmarking module 260 may be communicativelycoupled to and/or configured to operate in the task assignment system200 via other modules such as the task assignment module 210 and/or thehistorical assignment module 250. The benchmarking module 260 maybenchmark the relative performance of two or more pairing strategies(e.g., FIFO, PBR, BP, etc.) using historical assignment information,which may be received from, for example, the historical assignmentmodule 250. In some embodiments, the benchmarking module 260 may performother functions, such as establishing a benchmarking schedule forcycling among various pairing strategies, tracking cohorts (e.g., baseand measurement groups of historical assignments), etc. Benchmarking isdescribed in detail for the contact center context in, e.g., U.S. Pat.No. 9,712,676, which is hereby incorporated by reference herein.

In some embodiments, the benchmarking module 260 may output or otherwisereport or use the relative performance measurements. The relativeperformance measurements may be used to assess the quality of the taskassignment strategy to determine, for example, whether a different taskassignment strategy (or a different pairing model) should be used, or tomeasure the overall performance (or performance gain) that was achievedwithin the task assignment system 200 while it was optimized orotherwise configured to use one task assignment strategy instead ofanother.

FIG. 3 shows a contact assignment method 300 according to embodiments ofthe present disclosure. Contact assignment method 300 may begin at block310. At block 310, the contact assignment method 300 may determine if acontact had a prior interaction with a contact center system (e.g., taskassignment system 200). If the contact assignment method 300 determinesthat the contact had a prior interaction with the contact center system,the contact assignment method 300 may then proceed to block 320. Atblock 320, the contact assignment method 300 may assign the contact toan agent based on information associated with the prior interaction. Insome embodiment, the information associated with the contact's priorinteraction may include an amount of time that has elapsed since thecontact's prior interaction with the contact center system, an amount oftime that elapsed between the contact's prior interaction and aninteraction of the contact with the contact center system that precedesthe prior interaction, a time duration of the contact's priorinteraction, and/or an average time duration of the contact's priorinteraction and one or more interactions of the contact with the contactcenter system that precede the prior interaction. In other embodiments,the information associated with the contact's prior interaction mayinclude one or more outcomes from the prior interaction, and/or a mostcommon outcome from among the prior interaction and one or moreinteractions of the contact with the contact center system that precedethe prior interaction. In yet other embodiments, the informationassociated with the contact's prior interaction may include a type, apurpose, a context, or a queue of the prior interaction, and/or a mostcommon type, a most common purpose, a most common context, or a mostcommon queue among the prior interaction and one or more interactions ofthe contact with the contact center system that precede the priorinteraction

At this point it should be noted that task assignment in accordance withthe present disclosure as described above may involve the processing ofinput data and the generation of output data to some extent. This inputdata processing and output data generation may be implemented inhardware or software. For example, specific electronic components may beemployed in a behavioral pairing module or similar or related circuitryfor implementing the functions associated with task assignment inaccordance with the present disclosure as described above.Alternatively, one or more processors operating in accordance withinstructions may implement the functions associated with task assignmentin accordance with the present disclosure as described above. If such isthe case, it is within the scope of the present disclosure that suchinstructions may be stored on one or more non-transitory processorreadable storage media (e.g., a magnetic disk or other storage medium),or transmitted to one or more processors via one or more signalsembodied in one or more carrier waves.

The present disclosure is not to be limited in scope by the specificembodiments described herein. Indeed, other various embodiments of andmodifications to the present disclosure, in addition to those describedherein, will be apparent to those of ordinary skill in the art from theforegoing description and accompanying drawings. Thus, such otherembodiments and modifications are intended to fall within the scope ofthe present disclosure. Further, although the present disclosure hasbeen described herein in the context of at least one particularimplementation in at least one particular environment for at least oneparticular purpose, those of ordinary skill in the art will recognizethat its usefulness is not limited thereto and that the presentdisclosure may be beneficially implemented in any number of environmentsfor any number of purposes. Accordingly, the claims set forth belowshould be construed in view of the full breadth and spirit of thepresent disclosure as described herein.

1. A method for pairing contacts and agents in a contact center systemcomprising: assigning, by at least one computer processorcommunicatively coupled to and configured to operate in the contactcenter system, a contact to an agent based on information associatedwith a prior interaction of the contact with the contact center system,wherein the assigning results in a less favorable outcome for thecontact assigned to the agent and an increase in an overall performanceof the contact center system.
 2. The method of claim 1, wherein theinformation includes an amount of time that has elapsed since the priorinteraction.
 3. The method of claim 1, wherein the information includesan amount of time that elapsed between the prior interaction and aninteraction of the contact with the contact center system that precedesthe prior interaction.
 4. The method of claim 1, wherein the informationincludes a time duration of the prior interaction.
 5. The method ofclaim 1, wherein the information includes an average time duration ofthe prior interaction and one or more interactions of the contact withthe contact center system that precede the prior interaction.
 6. Themethod of claim 1, wherein the information includes one or more outcomesfrom the prior interaction.
 7. The method of claim 1, wherein theinformation includes a most common outcome from among the priorinteraction and one or more interactions of the contact with the contactcenter system that precede the prior interaction.
 8. The method of claim1, wherein the information includes at least one of a type, a purpose, acontext, and a queue of the prior interaction.
 9. The method of claim 1,wherein the information includes at least one of a most common type, amost common purpose, a most common context, and a most common queueamong the prior interaction and one or more interactions of the contactwith the contact center system that precede the prior interaction.
 10. Amethod for pairing contacts and agents in a contact center systemcomprising: determining, by at least one computer processorcommunicatively coupled to and configured to operate in the contactcenter system, whether a contact had a prior interaction with thecontact center system; and assigning, by the at least one computerprocessor, the contact to an agent based on information associated withthe prior interaction, wherein the assigning results in a less favorableoutcome for the contact assigned to the agent and an increase in anoverall performance of the contact center system.
 11. A system forbehavioral pairing in a contact center system comprising: at least onecomputer processor communicatively coupled to and configured to operatein the contact center system, wherein the at least one computerprocessor is further configured to: assign a contact to an agent basedon information associated with a prior interaction of the contact withthe contact center system, wherein assigning the contact to the agentresults in a less favorable outcome for the contact assigned to theagent and an increase in an overall performance of the contact centersystem.
 12. The system of claim 11, wherein the information includes anamount of time that has elapsed since the prior interaction.
 13. Thesystem of claim 11, wherein the information includes an amount of timethat elapsed between the prior interaction and an interaction of thecontact with the contact center system that precedes the priorinteraction.
 14. The system of claim 11, wherein the informationincludes a time duration of the prior interaction.
 15. The system ofclaim 11, wherein the information includes an average time duration ofthe prior interaction and one or more interactions of the contact withthe contact center system that precede the prior interaction.
 16. Thesystem of claim 11, wherein the information includes one or moreoutcomes from the prior interaction.
 17. The system of claim 11, whereinthe information includes a most common outcome from among the priorinteraction and one or more interactions of the contact with the contactcenter system that precede the prior interaction.
 18. The system ofclaim 11, wherein the information includes at least one of a type, apurpose, a context, and a queue of the prior interaction.
 19. The systemof claim 11, wherein the information includes at least one of a mostcommon type, a most common purpose, a most common context, and a mostcommon queue among the prior interaction and one or more interactions ofthe contact with the contact center system that precede the priorinteraction.
 20. An article of manufacture for behavioral pairing in acontact center system comprising: a non-transitory processor readablemedium; and instructions stored on the medium; wherein the instructionsare configured to be readable from the medium by at least one computerprocessor communicatively coupled to and configured to operate in thecontact center system and thereby cause the at least one computerprocessor to operate so as to: assign a contact to an agent based oninformation associated with a prior interaction of the contact with thecontact center system, wherein assigning the contact to the agentresults in a less favorable outcome for the contact assigned to theagent and an increase in an overall performance of the contact centersystem.